2D spectral-temporal fitting of synthetic fMRS data improves the precision of fitted glutamate temporal dynamics parameters three-fold

It has been suggested that fitting dynamic MRS data in tandem (2D fitting) should be more precise than conventional 1D fitting, without impairing its accuracy. Functional MRS (fMRS) is a dynamic method used for detecting endogenous metabolic changes in the brain. In this work, we implemented a 2D spectral-temporal fitting framework for the synthetic fMRS data. Preliminary experiments confirm that 2D fitting improves precision approximately three-fold compared to the conventional 1D fitting in terms of fMRS data.